By 23, he had a Ph.D. in math from the University of Illinois at
Chicago, and, he says, he wanted to find a job where he had a
real-world impact.

So Krzyzanowski, now 25, joined a little-known
financial-technology startup called Avant.

The Chicago-based online lending platform is one of a handful of
startups that are looking to overturn the consumer-loan market by
finding ways to approve loans faster than banks. For some people,
Avant can approve a loan the same day.

Founded in 2012, Avant is the fastest-growing online marketplace
lender, having raised more than $1.6 billion in three years. It's
also a member of the unicorn club, with a valuation of more than
$2 billion.

A couple of years ago, it might have seemed a risky place to
start a career. Krzyzanowski's telling of his experience at Avant
hits all the perks of working at a tech startup, starting with
the drive of his coworkers.

The startup 'drive'

"Even in grad school, where you have people that are from a wide
variety of backgrounds and are generally motivated, I hadn't
really seen the kind of drive that you do in the first few years
of a really fast-growing venture," he said.

While his academic background is in math and statistics, at Avant
he manages the programmers.

Inside Avant's Chicago
headquarters.Ramzi
Dreessen/Avant

Krzyzanowski likes being able to wear many hats at Avant, another
perk of being at a small operation. He's also able to see the
direct impact of his work.

"Whenever we have customers streaming, the work that I do and the
work that the people I work with do — it's constantly making
decisions and at every second it's actually having an impact on
our customers," Krzyzanowski said.

"So without that kind of tethering to the real world, it's hard
to justify any work you're doing, and I found that to be true
moving from academia into the industry."

What is data engineering?

Krzyzanowski's analytics team essentially transforms any insights
that the company has on potential customers into useful data
points that can be used to analyze their worthiness as a
borrower.

"What we do boils down to making decisions — but making them
better and making them faster," Krzyzanowski said.

Avant must be able to decide whether customers are fraudulent.
(There are two kinds of fraud, Krzyzanowski said: soft fraud,
such as using a current credit rating to get a one-time loan,
even while knowing that, for example, some large debt may be
coming in; and hard fraud, like identity theft.)

Jessica
Smith/Avant

His team gauges that by using "offline"
tools and machine-learning techniques to analyze hundreds or
even thousands of variables to assess fraud risks. Most lenders
are able to analyze only dozens of variables.

"Effectively what we're able to do is take these complicated
algorithms and then translate them into code that can make the
decision instantly," Krzyzanowski said.